{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multiclass Support Vector Machine exercise\n",
    "\n",
    "*Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more details see the [assignments page](http://vision.stanford.edu/teaching/cs231n/assignments.html) on the course website.*\n",
    "\n",
    "In this exercise you will:\n",
    "    \n",
    "- implement a fully-vectorized **loss function** for the SVM\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** using numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Run some setup code for this notebook.\n",
    "\n",
    "import random\n",
    "import numpy as np\n",
    "from cs231n.data_utils import load_CIFAR10\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from __future__ import print_function\n",
    "\n",
    "# This is a bit of magic to make matplotlib figures appear inline in the\n",
    "# notebook rather than in a new window.\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# Some more magic so that the notebook will reload external python modules;\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CIFAR-10 Data Loading and Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (50000, 32, 32, 3)\n",
      "Training labels shape:  (50000,)\n",
      "Test data shape:  (10000, 32, 32, 3)\n",
      "Test labels shape:  (10000,)\n"
     ]
    }
   ],
   "source": [
    "# Load the raw CIFAR-10 data.\n",
    "cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "\n",
    "# As a sanity check, we print out the size of the training and test data.\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Training labels shape: ', y_train.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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QVmohTW0+v5XaKIXSlf36AEokjOmhVzEGXx8y6nqMarTwqBewqyYH8p//lz/i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8EB5tkUdW6lhfIYyAoNi023fMuFL6jfnlb4/NEWAGA8LJAnFPgWlo3RiGvL9noQTJ0uMo10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FEPjg9n0AQJqVeOEF3d4cHKLqB6eDTlcbZWdnZxgTlRx4FgQZygcHJ3j9+98DAOzffg82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\nDt0cCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff650f70150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize some examples from the dataset.\n",
    "# We show a few examples of training images from each class.\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "num_classes = len(classes)\n",
    "samples_per_class = 7\n",
    "for y, cls in enumerate(classes):\n",
    "    idxs = np.flatnonzero(y_train == y)\n",
    "    idxs = np.random.choice(idxs, samples_per_class, replace=False)\n",
    "    for i, idx in enumerate(idxs):\n",
    "        plt_idx = i * num_classes + y + 1\n",
    "        plt.subplot(samples_per_class, num_classes, plt_idx)\n",
    "        plt.imshow(X_train[idx].astype('uint8'))\n",
    "        plt.axis('off')\n",
    "        if i == 0:\n",
    "            plt.title(cls)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 32, 32, 3)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 32, 32, 3)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 32, 32, 3)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "# Split the data into train, val, and test sets. In addition we will\n",
    "# create a small development set as a subset of the training data;\n",
    "# we can use this for development so our code runs faster.\n",
    "num_training = 49000\n",
    "num_validation = 1000\n",
    "num_test = 1000\n",
    "num_dev = 500\n",
    "\n",
    "# Our validation set will be num_validation points from the original\n",
    "# training set.\n",
    "mask = range(num_training, num_training + num_validation)\n",
    "X_val = X_train[mask]\n",
    "y_val = y_train[mask]\n",
    "\n",
    "# Our training set will be the first num_train points from the original\n",
    "# training set.\n",
    "mask = range(num_training)\n",
    "X_train = X_train[mask]\n",
    "y_train = y_train[mask]\n",
    "\n",
    "# We will also make a development set, which is a small subset of\n",
    "# the training set.\n",
    "mask = np.random.choice(num_training, num_dev, replace=False)\n",
    "X_dev = X_train[mask]\n",
    "y_dev = y_train[mask]\n",
    "\n",
    "# We use the first num_test points of the original test set as our\n",
    "# test set.\n",
    "mask = range(num_test)\n",
    "X_test = X_test[mask]\n",
    "y_test = y_test[mask]\n",
    "\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (49000, 3072)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Test data shape:  (1000, 3072)\n",
      "dev data shape:  (500, 3072)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: reshape the image data into rows\n",
    "X_train = np.reshape(X_train, (X_train.shape[0], -1))\n",
    "X_val = np.reshape(X_val, (X_val.shape[0], -1))\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], -1))\n",
    "X_dev = np.reshape(X_dev, (X_dev.shape[0], -1))\n",
    "\n",
    "# As a sanity check, print out the shapes of the data\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('dev data shape: ', X_dev.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 130.64189796  135.98173469  132.47391837  130.05569388  135.34804082\n",
      "  131.75402041  130.96055102  136.14328571  132.47636735  131.48467347]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff64c5b99d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Preprocessing: subtract the mean image\n",
    "# first: compute the image mean based on the training data\n",
    "mean_image = np.mean(X_train, axis=0)\n",
    "print(mean_image[:10]) # print a few of the elements\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.imshow(mean_image.reshape((32,32,3)).astype('uint8')) # visualize the mean image\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# second: subtract the mean image from train and test data\n",
    "X_train -= mean_image\n",
    "X_val -= mean_image\n",
    "X_test -= mean_image\n",
    "X_dev -= mean_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(49000, 3073) (1000, 3073) (1000, 3073) (500, 3073)\n"
     ]
    }
   ],
   "source": [
    "# third: append the bias dimension of ones (i.e. bias trick) so that our SVM\n",
    "# only has to worry about optimizing a single weight matrix W.\n",
    "X_train = np.hstack([X_train, np.ones((X_train.shape[0], 1))])\n",
    "X_val = np.hstack([X_val, np.ones((X_val.shape[0], 1))])\n",
    "X_test = np.hstack([X_test, np.ones((X_test.shape[0], 1))])\n",
    "X_dev = np.hstack([X_dev, np.ones((X_dev.shape[0], 1))])\n",
    "\n",
    "print(X_train.shape, X_val.shape, X_test.shape, X_dev.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SVM Classifier\n",
    "\n",
    "Your code for this section will all be written inside **cs231n/classifiers/linear_svm.py**. \n",
    "\n",
    "As you can see, we have prefilled the function `compute_loss_naive` which uses for loops to evaluate the multiclass SVM loss function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 9.255021\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the naive implementation of the loss we provided for you:\n",
    "from cs231n.classifiers.linear_svm import svm_loss_naive\n",
    "import time\n",
    "\n",
    "# generate a random SVM weight matrix of small numbers\n",
    "W = np.random.randn(3073, 10) * 0.0001 \n",
    "\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "print('loss: %f' % (loss, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `grad` returned from the function above is right now all zero. Derive and implement the gradient for the SVM cost function and implement it inline inside the function `svm_loss_naive`. You will find it helpful to interleave your new code inside the existing function.\n",
    "\n",
    "To check that you have correctly implemented the gradient correctly, you can numerically estimate the gradient of the loss function and compare the numeric estimate to the gradient that you computed. We have provided code that does this for you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: -17.940325 analytic: -17.940325, relative error: 1.114411e-12\n",
      "numerical: 9.348851 analytic: 9.348851, relative error: 2.868751e-11\n",
      "numerical: -17.510312 analytic: -17.510312, relative error: 1.015457e-11\n",
      "numerical: -11.195977 analytic: -11.195977, relative error: 4.921293e-11\n",
      "numerical: 0.326703 analytic: 0.326703, relative error: 2.606861e-10\n",
      "numerical: 13.916159 analytic: 13.916159, relative error: 1.885207e-11\n",
      "numerical: 15.405188 analytic: 15.405188, relative error: 1.508991e-12\n",
      "numerical: 1.183527 analytic: 1.183527, relative error: 9.833907e-11\n",
      "numerical: 22.896302 analytic: 22.896302, relative error: 5.822504e-12\n",
      "numerical: 18.046345 analytic: 18.046345, relative error: 5.746423e-12\n",
      "numerical: -43.964686 analytic: -43.964686, relative error: 4.026518e-12\n",
      "numerical: -58.090757 analytic: -58.090757, relative error: 8.146855e-12\n",
      "numerical: -24.673229 analytic: -24.673229, relative error: 6.280799e-12\n",
      "numerical: -16.995245 analytic: -16.995245, relative error: 1.270774e-11\n",
      "numerical: -8.686808 analytic: -8.686808, relative error: 3.301864e-11\n",
      "numerical: 2.618196 analytic: 2.618196, relative error: 5.919343e-11\n",
      "numerical: 2.594395 analytic: 2.594395, relative error: 1.865268e-10\n",
      "numerical: 6.277037 analytic: 6.277037, relative error: 2.585918e-12\n",
      "numerical: 20.634753 analytic: 20.634753, relative error: 1.769285e-11\n",
      "numerical: 13.922230 analytic: 13.922230, relative error: 2.980918e-12\n"
     ]
    }
   ],
   "source": [
    "# Once you've implemented the gradient, recompute it with the code below\n",
    "# and gradient check it with the function we provided for you\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.0)\n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should match\n",
    "# almost exactly along all dimensions.\n",
    "from cs231n.gradient_check import grad_check_sparse\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 0.0)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)\n",
    "\n",
    "# do the gradient check once again with regularization turned on\n",
    "# you didn't forget the regularization gradient did you?\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 5e1)\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 5e1)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inline Question 1:\n",
    "It is possible that once in a while a dimension in the gradcheck will not match exactly. What could such a discrepancy be caused by? Is it a reason for concern? What is a simple example in one dimension where a gradient check could fail? *Hint: the SVM loss function is not strictly speaking differentiable*\n",
    "\n",
    "**Your Answer:** *fill this in.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss: 9.255021e+00 computed in 0.123901s\n",
      "Vectorized loss: 9.255021e+00 computed in 0.008583s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Next implement the function svm_loss_vectorized; for now only compute the loss;\n",
    "# we will implement the gradient in a moment.\n",
    "tic = time.time()\n",
    "loss_naive, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss: %e computed in %fs' % (loss_naive, toc - tic))\n",
    "\n",
    "from cs231n.classifiers.linear_svm import svm_loss_vectorized\n",
    "tic = time.time()\n",
    "loss_vectorized, _ = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss: %e computed in %fs' % (loss_vectorized, toc - tic))\n",
    "\n",
    "# The losses should match but your vectorized implementation should be much faster.\n",
    "print('difference: %f' % (loss_naive - loss_vectorized))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss and gradient: computed in 0.129421s\n",
      "Vectorized loss and gradient: computed in 0.002845s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Complete the implementation of svm_loss_vectorized, and compute the gradient\n",
    "# of the loss function in a vectorized way.\n",
    "\n",
    "# The naive implementation and the vectorized implementation should match, but\n",
    "# the vectorized version should still be much faster.\n",
    "tic = time.time()\n",
    "_, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "tic = time.time()\n",
    "_, grad_vectorized = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "# The loss is a single number, so it is easy to compare the values computed\n",
    "# by the two implementations. The gradient on the other hand is a matrix, so\n",
    "# we use the Frobenius norm to compare them.\n",
    "difference = np.linalg.norm(grad_naive - grad_vectorized, ord='fro')\n",
    "print('difference: %f' % difference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stochastic Gradient Descent\n",
    "\n",
    "We now have vectorized and efficient expressions for the loss, the gradient and our gradient matches the numerical gradient. We are therefore ready to do SGD to minimize the loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 406.231497\n",
      "iteration 100 / 1500: loss 240.426514\n",
      "iteration 200 / 1500: loss 147.088157\n",
      "iteration 300 / 1500: loss 90.554818\n",
      "iteration 400 / 1500: loss 57.032476\n",
      "iteration 500 / 1500: loss 36.064814\n",
      "iteration 600 / 1500: loss 24.297829\n",
      "iteration 700 / 1500: loss 16.130737\n",
      "iteration 800 / 1500: loss 12.096695\n",
      "iteration 900 / 1500: loss 9.100409\n",
      "iteration 1000 / 1500: loss 7.513749\n",
      "iteration 1100 / 1500: loss 6.162538\n",
      "iteration 1200 / 1500: loss 5.767268\n",
      "iteration 1300 / 1500: loss 5.490698\n",
      "iteration 1400 / 1500: loss 4.921053\n",
      "That took 3.496522s\n"
     ]
    }
   ],
   "source": [
    "# In the file linear_classifier.py, implement SGD in the function\n",
    "# LinearClassifier.train() and then run it with the code below.\n",
    "from cs231n.classifiers import LinearSVM\n",
    "svm = LinearSVM()\n",
    "tic = time.time()\n",
    "loss_hist = svm.train(X_train, y_train, learning_rate=1e-7, reg=2.5e4,\n",
    "                      num_iters=1500, verbose=True)\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Rpzcrm9Tc0et3FAAAEEcoaD666IQi9UecXni71u8oAAAgjlDQfLSoNEfhYECbWJcTAAAM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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff64cc96610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A useful debugging strategy is to plot the loss as a function of\n",
    "# iteration number:\n",
    "plt.plot(loss_hist)\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 0.383490\n",
      "validation accuracy: 0.392000\n"
     ]
    }
   ],
   "source": [
    "# Write the LinearSVM.predict function and evaluate the performance on both the\n",
    "# training and validation set\n",
    "y_train_pred = svm.predict(X_train)\n",
    "print('training accuracy: %f' % (np.mean(y_train == y_train_pred), ))\n",
    "y_val_pred = svm.predict(X_val)\n",
    "print('validation accuracy: %f' % (np.mean(y_val == y_val_pred), ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "cs231n/classifiers/linear_svm.py:79: RuntimeWarning: overflow encountered in subtract\n",
      "  margins = np.maximum(0,scores-np.reshape(correct_class_score,[num_train,1])+1)\n",
      "cs231n/classifiers/linear_svm.py:79: RuntimeWarning: invalid value encountered in subtract\n",
      "  margins = np.maximum(0,scores-np.reshape(correct_class_score,[num_train,1])+1)\n",
      "cs231n/classifiers/linear_svm.py:98: RuntimeWarning: invalid value encountered in greater\n",
      "  margins01 = 1 * (margins > 0)\n",
      "cs231n/classifiers/linear_svm.py:102: RuntimeWarning: overflow encountered in multiply\n",
      "  dW += reg * W\n",
      "cs231n/classifiers/linear_classifier.py:72: RuntimeWarning: invalid value encountered in subtract\n",
      "  #                       END OF YOUR CODE                                #\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr 1.000000e-07 reg 2.500000e+04 train accuracy: 0.380184 val accuracy: 0.387000\n",
      "lr 1.000000e-07 reg 5.000000e+04 train accuracy: 0.369490 val accuracy: 0.381000\n",
      "lr 5.000000e-05 reg 2.500000e+04 train accuracy: 0.146204 val accuracy: 0.146000\n",
      "lr 5.000000e-05 reg 5.000000e+04 train accuracy: 0.100265 val accuracy: 0.087000\n",
      "best validation accuracy achieved during cross-validation: 0.387000\n"
     ]
    }
   ],
   "source": [
    "# Use the validation set to tune hyperparameters (regularization strength and\n",
    "# learning rate). You should experiment with different ranges for the learning\n",
    "# rates and regularization strengths; if you are careful you should be able to\n",
    "# get a classification accuracy of about 0.4 on the validation set.\n",
    "learning_rates = [1e-7, 5e-5]\n",
    "regularization_strengths = [2.5e4, 5e4]\n",
    "\n",
    "# results is dictionary mapping tuples of the form\n",
    "# (learning_rate, regularization_strength) to tuples of the form\n",
    "# (training_accuracy, validation_accuracy). The accuracy is simply the fraction\n",
    "# of data points that are correctly classified.\n",
    "results = {}\n",
    "best_val = -1   # The highest validation accuracy that we have seen so far.\n",
    "best_svm = None # The LinearSVM object that achieved the highest validation rate.\n",
    "\n",
    "################################################################################\n",
    "# TODO:                                                                        #\n",
    "# Write code that chooses the best hyperparameters by tuning on the validation #\n",
    "# set. For each combination of hyperparameters, train a linear SVM on the      #\n",
    "# training set, compute its accuracy on the training and validation sets, and  #\n",
    "# store these numbers in the results dictionary. In addition, store the best   #\n",
    "# validation accuracy in best_val and the LinearSVM object that achieves this  #\n",
    "# accuracy in best_svm.                                                        #\n",
    "#                                                                              #\n",
    "# Hint: You should use a small value for num_iters as you develop your         #\n",
    "# validation code so that the SVMs don't take much time to train; once you are #\n",
    "# confident that your validation code works, you should rerun the validation   #\n",
    "# code with a larger value for num_iters.                                      #\n",
    "################################################################################\n",
    "for lr in learning_rates:\n",
    "    for reg in regularization_strengths:\n",
    "        svm = LinearSVM()\n",
    "        svm.train(X_train, y_train, lr, reg, num_iters=2000, verbose=False)\n",
    "        y_train_pred = svm.predict(X_train)\n",
    "        y_val_pred = svm.predict(X_val)\n",
    "        training_accuracy = np.mean(y_train == y_train_pred)\n",
    "        validation_accuracy = np.mean(y_val == y_val_pred)\n",
    "        results[(lr,reg)] = (training_accuracy,validation_accuracy)\n",
    "        if validation_accuracy > best_val:\n",
    "            best_val = validation_accuracy\n",
    "            best_svm = svm\n",
    "################################################################################\n",
    "#                              END OF YOUR CODE                                #\n",
    "################################################################################\n",
    "    \n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "    train_accuracy, val_accuracy = results[(lr, reg)]\n",
    "    print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "                lr, reg, train_accuracy, val_accuracy))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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32/cPZtt6VW4qWG88T4+dRURExAjRokvP51OWqkgaR1GqckFtA0lTKS6Eerft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\nkp2IiIjoakl2IiIioqsl2YmIiIiu9v8BytvQd7Qg1+QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff648de1810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the cross-validation results\n",
    "import math\n",
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linear SVM on raw pixels final test set accuracy: 0.388000\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the best svm on test set\n",
    "y_test_pred = best_svm.predict(X_test)\n",
    "test_accuracy = np.mean(y_test == y_test_pred)\n",
    "print('linear SVM on raw pixels final test set accuracy: %f' % test_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IqtsCY+EOy3lzeN49q/HsivJfvV9j7HQxVCwiOS/OUM+GPPVWK7iy+lvyFvQO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tKPWgglugui1wJSD/mkeii23z3DBRnWpaAx5mT66RAd5D4nM0kf9Y8ilLsgGjIhms+s0XZHZKbW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\nK+kSlAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff648ded5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the learned weights for each class.\n",
    "# Depending on your choice of learning rate and regularization strength, these may\n",
    "# or may not be nice to look at.\n",
    "w = best_svm.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(32, 32, 3, 10)\n",
    "w_min, w_max = np.min(w), np.max(w)\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "    plt.subplot(2, 5, i + 1)\n",
    "      \n",
    "    # Rescale the weights to be between 0 and 255\n",
    "    wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "    plt.imshow(wimg.astype('uint8'))\n",
    "    plt.axis('off')\n",
    "    plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inline question 2:\n",
    "Describe what your visualized SVM weights look like, and offer a brief explanation for why they look they way that they do.\n",
    "\n",
    "**Your answer:** *fill this in*"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
